Department of Electrical and Electronics Engineering
Permanent URI for this collectionhttp://localhost:4000/handle/123456789/1925
Browse
87 results
Search Results
Item Digital twin simulation and comparative study to understand the microgrid operation and control(IEEE, 2025-01) Mathur, Hitesh Datt; Gautam, Aditya R.Solar photovoltaic (PV) microgrid (MG) systems are the future of the growing electrical industry. However, these systems have a dependency on the environment. To mitigate this dependency, better control and technologies are required. The digital twin (DT) technology can be utilized to make these MGs more sustainable and promising. In this paper, the DT of the installed MG has been developed on the Simulink platform. The irradiance data, and load power consumption data have been used as input for the DT of the MG. Moreover, it is found that the DT of the MG is working stably with the given data. On the output side, the grid power data of the physical MG has been compared with the output grid power of DT. Further, it has been found that the solar power generation, load power consumption data, and grid power data have matched the results of the physical MG.Item The development and potential of green hydrogen in India(IEEE, 2025-02) Mathur, Hitesh DattThe search for alternative fuel sources has been driven by the need for a sustainable energy future. Most current forms of energy produce vast amounts of carbon content and release it into the atmosphere. This has led to a global rise in temperature levels and is seen as the immediate threat faced by all humans. In a bid to tackle this, renewable energy and green hydrogen are seen as the leading solutions. As many countries, including India, have set goals for green hydrogen, we have conducted this study to identify what the scenario is in other countries, as well as what the scenario is in India. Our focus is on Green Hydrogen, the Hydrogen Economy, Climate Change, Production of Green Hydrogen, Hydrogen Storage, and Potential of Green Hydrogen in India.Item Fuzzy-based fractional order control for effective frequency regulation(IEEE, 2025-05) Mishra, Puneet; Mathur, Hitesh DattThe objective of the presented work is to investigate the application of a fuzzy fractional order PID (fuzzy FOPID) controller in a two-area tied hybrid power system. This consists of integrating thermoelectric power plants that have been heated again, together with unpredictable renewable energy sources, inside a single control region. Additionally, there are hydropower plants in another control area. Renewable energy sources encompass wind power, solar thermal energy, and fuel cells. To simulate a realistic situation, the thermal and hydro systems are equipped with a generation rate constraint (GRC) and a governor dead band (GDB). Furthermore, the turbine incorporates boiler dynamics (BD), and both control regions experience a stochastic variation in load. Extensive simulations have shown that the Fuzzy FOPID control structure has superior performance compared to FOPID and PID controllers, as measured by the performance index. Robustness may be demonstrated by doing sensitivity analysis on system parameters, including the speed control parameter, GDB, GRC, and random load perturbation, for substantial changes. Moreover, the system’s performance has been assessed, considering the delay in communication, which significantly degrades the performance. Extensive simulations have shown that the fuzzy-based FOPID controller surpasses other controllers in terms of resilience and accuracy. Therefore, it may be considered a practical solution to the load frequency control problem.Item A novel particle swarm optimization based plant-in-loop tuning method for PI controller of integrated power converters(IEEE, 2025-04) Yadav, Sisir Kumar; Patel, Ashish; Mathur, Hitesh DattIntegrated Power Converters such as Shunt Active Power Filters (APFs), when integrated with renewable sources like solar PV, offer a more capable and cost-effective solution for both their core function and for feeding the renewable power to the grid. Shunt APF is generally integrated with PV arrays on the common DC link to compensate for power quality issues and feed solar PV power simultaneously. However, the regulation of the DC link, which is the foundation of the operation of such converters, can be more challenging due to the inclusion of PV intermittency. So, the PI controller, mostly used for DC link regulation, should be tuned optimally considering the variable operating conditions. Most tuning methods, whether offline or online, rely on mathematical modeling of the converter and are affected by inherent inaccuracies. Therefore, this work proposes an in-plant PI tuning method for shunt APF, which doesn’t require mathematical modeling and can be implemented in realtime within the actual plant and operating conditions therein. The method tunes the PI controller without having to relax the limits on its output, which are required for the safety of the hardware. The proposed method has been validated using realtime simulation and hardware setup of the PV-integrated shunt APF, and, in both cases, the method shows superior performance in regulating the DC link voltage of the integrated converter system under various operating conditions.Item Optimal scheduling of mobile and stationary electric vehicle charging stations in a distribution system with stochastic loading(Elsevier, 2025-07) Mishra, Puneet; Mathur, Hitesh DattDue to surge in the use of electric vehicles (EVs), electric vehicle charging station (EVCS) load modelling emerges to be vital in designing or revamping existing EV charging facilities. The present work addresses this optimal scheduling problem by proposing a novel probabilistic model to predict the optimum demand at a charging station for fixed time duration and thereafter for variable durations using dynamic fault tree analysis considering the charging urgency of the vehicles. To cater to the increased load demand due to enhanced EV penetration and to mitigate its associated technical challenges, incorporation of Mobile Charging Station (MCS) is proposed in the present work. However, placement of MCS poses a significant challenge of their optimal siting and scheduling. This has been achieved by identifying priority areas for their positioning from a proposed Mobile Charging Station Allocation Indicator (MCSAI) computed based on escalated requirement at an EVCS. Extensive investigations have been conducted for placement of combination of fixed and mobile EVCS in a standard IEEE 33 and 85 bus distribution system and it is shown that the resultant hybrid system leads to a significant improvement of more than 5 %, 15 % and 25, 30 % respectively as measured by indices such as line loss reduction index voltage profile improvement index.Item Performance assessment of a distribution system with electric vehicle charging station and forecasted loads(Springer, 2025-05) Mishra, Puneet; Mathur, Hitesh DattA trend towards green transportation causes huge escalation in the use of electric vehicles. Therefore, proper evaluation of the burden on a charging changing station is immensely essential. This work propounds a novel technique based on probabilistic estimation of the total demand at an Electric Vehicle Charging Station (EVCS) for certain fixed hourly durations of time and then on the basis of vehicle categorisation dependent on the exigency of the vehicles. Based on the probabilistic estimation of EVCS loads, an optimum mix of charging stations is positioned strategically in an IEEE 33 bus distribution system designed on a methodology based on apparent power loss. The system with EVCS positioned at the optimal points is analysed with the help of two assessment indicators, namely line loss reduction index and voltage profile improvement index. The performance of the aforesaid system is strengthened by the addition of distributed generators at the aptly sited locations.Item A Single-Phase Grid-Tied Converter System Integrating Solar PV, Battery and Compensating Power Quality(IEEE, 2023) Patel, Ashish; Yadav, Sisir Kumar; Mathur, Hitesh DattSingle-phase inverters integrating battery storage and renewable energy sources are becoming popular among resi-dential electricity consumers because of the need for reliable and quality power, pollution reduction, and savings in electricity costs. Gird-connected inverters have a multi-mode operation and are preferable over isolated ones, but their high complexity and cost are a concern. Battery integration with such inverters requires a high-voltage battery bank, which increases the cost further. Also, most single-phase grid-tied inverters don't support power quality compensation. This paper proposes an integrated power converter system forming a single-phase home grid, addressing the above-mentioned issues. The proposed approach integrates a low-voltage battery (48V) at the DC link of the grid-tied inverter using a high-gain bidirectional converter. It also enhances the capability of the single-phase grid-tied inverter to compensate for the power quality issues such as reactive power and non-linear current of the load. The proposed system is validated using MATLAB/Simulink simulation.Item Novel optimal energy management with demand response for a real-time community microgrid(IEEE, 2023) Mathur, Hitesh Datt; Mishra, PuneetDue to the uncertain nature of renewable sources (RS), microgrids (MGs) are becoming inefficient and unreliable. Further, battery energy storage systems (BESS) ensure uninterrupted power supply in MGs. However, integrating BESS can increase MG's operating costs and make the system uneconomical. This paper proposes an optimal energy management (OEM) algorithm that can minimize MG's operating and maintenance (O&M) cost and improve the system's efficiency. In addition, to improve the system's reliability, the demand response (DR) strategy is integrated with the proposed OEM, i.e., OEM-DR. This strategy focuses on maximizing the utilization of RS and minimizing the dependency of MG on a grid, along with fulfilling the objectives of OEM. The formulated objective function is solved using linear programming (LP). In order to evaluate the efficacy of these strategies, the analysis is performed with the real-time data of three seasons, i.e., summer, winter, and rainy. The real-time data is obtained by the MG installed at the commercial building of BITS, Pilani, India. It is found from the results that with the OEM-DR, a significant decrement in operating cost, as well as power imported from the grid, is achieved.Item Real Time Data-based Demand Side Management Techniques for a Microgrid to Minify the Grid Dependency(IEEE, 2023) Mathur, Hitesh DattRenewable energy sources (RES) based microgrids (MGs) are the future of the growing electrical industry. Numerous government and private organizations are working in this sector to increase its penetration to the conventional electrical system. But this expanding industry is hindered by its intermittent nature and expensive cost of storage. To make MG based electrical industry sector more sustainable and promising, a technique, demand side management (DSM) is integrated with the system. This paper proposes the development of two DSM based techniques i.e., non-essential load shifting technique (NELST) and direct load shifting technique (DLST) to maximize the solar photovoltaic (PV) usage and to minimize the operational cost of the MG. These techniques were analyzed with the real time data collected from the installed MG at BITS Pilani, Pilani campus, India and it was found that there was a significant decrement in grid import (GI) and grid export (GE). It was observed from the results that there was a significant increase in the solar PV utilization and significant decrease in the operational cost of the MG.Item Optimal Siting and Sizing of Renewable Energy Sources in Distribution System(Springer, 2023-07) Mathur, Hitesh DattAn optimal siting and sizing of renewable energy sources (RES) play a substantial role in achieving the efficient operation and planning of the distribution system. It majorly affects the active power loss and voltage stability of the system. Therefore, this study formulates a multi-objective function that optimally allocates and sizes the RES in the distribution network by minimizing the total active power losses (TAPL) and voltage deviation (VD) of the network buses. The proposed algorithm is validated on an IEEE 69-bus model having two types of loads, i.e. consumer load and charging load of an electric vehicle. The consumer load is modelled as a polynomial type of load, and a total of four electric vehicle charging stations (EVSs) are integrated into the model. The formulated objective function also optimally allocates these four EVSs to minimize the TAPL and VD of the system. The objective function is minimized using four different optimization techniques, i.e. genetic algorithm (GA), grey wolf optimizer (GWO), particle swarm optimization (PSO), and hybrid particle swarm grey wolf optimization (HPSGWO). The simulation studies showed that the HPSGWO is superior to all other algorithms as it provides the solution having the lowest TAPL and VD in the system.